Characterization of Using Hybrid Beamforming in mmWave Virtual Reality

TL;DR

This paper investigates hybrid beamforming in mmWave WLANs for virtual reality, proposing a utility function for resource management that optimizes QoS by considering delays and channel conditions, with high accuracy in modeling.

Contribution

It introduces a closed-form multi-attribute utility function incorporating delays and hybrid beamforming for VR in mmWave WLANs, validated with high accuracy.

Findings

Hybrid beamforming reduces hardware complexity in mmWave VR systems.

The utility function effectively models QoS considering delays and channel gain.

Achieved 95.4% accuracy in channel modeling compared to ns3 simulations.

Abstract

Wireless Virtual Reality (VR) is increasingly in demand in Wireless LANs (WLANs). In this paper, a utility function for resource management in wireless VR is proposed. Maximizing the sum rate metric in transmitting VR audio or videos is an important factor for ascertaining low latency in obtaining QoS requirement of users in VR, so forth mmWave frequency band in WLAN technology should be used. This frequency band is presented in IEEE 802.11ad/ay. Resource access method in IEEE 802.11ay standard is MultiUser MIMO (MU-MIMO) with OFDM modulation. Operating at mmWave frequency band is equal to use massive number of antenna to enhance the received power in (Line of Sight) LoS direction by inducing sever propagation with small wavelength. Also for reducing the complexity of hardware in mmWave technology, designers should select some number of connected phase shifters to each antenna element by hybrid beamforming method. Processing delay, transmission delay and queue delay should be considered in acquiring QoS metric in terms of utility function. The optimal closed form expression of the multi-attribute utility function is based on these delays that are calculated by downlink and uplink rates in assistant with hybrid beamforming. Trends of transmission delay and multi-attribute utility function in various Es/N0 values and different scenarios are analyzed. Based on these results, 95.4% accuracy in comparison with ns3 in uplink and downlink channel modeling in IEEE 802.11ay standard's indoor environment has been reported. Also, it is shown that min channel gain consideration can cause reduction in the value of the utility function and incursion in transmission delay in VR.